test page_type: sample languages:

• python

MLOps will help you to understand how to build a Continuous Integration and Continuous Delivery pipeline for an ML/AI project. We will be using the DevOps Project for build and release/deployment pipelines along with ML services for model retraining pipeline, model management and operationalization.

This template contains code and pipeline definitions for a machine learning project that demonstrates how to automate an end to end ML/AI workflow.

To deploy this solution in your subscription, follow the manual instructions in the getting started doc. Then optionally follow the guide for integrating your own code with this repository template.

You can find the details of the code and scripts in the repository here

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.